feat(ml): multi-agent context framework + v4 orchestrator prompt

Adds ml/agents/ — five specialised sub-agents (overdue_task, momentum,
time_of_day, recent_patterns, focus_area) each producing a prompt snippet
from user signals. A registry wires them up; the orchestrator prompt in
ml/serving/prompts.py synthesises their outputs into one tip via LiteLLM.

Also wires /api/agents route in the API and updates the Dockerfile to copy
the full ml/ tree with PYTHONPATH=/app so agent imports resolve correctly.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

ml/agents/__init__.py

@@ -0,0 +1,4 @@
+from .base import BaseAgent, AgentInput, AgentOutput
+from .registry import get_agent, all_agents
+
+__all__ = ["BaseAgent", "AgentInput", "AgentOutput", "get_agent", "all_agents"]